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https://www.bbc.co.uk/

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https://www.linkedin.com/in/magdapiatkowska/

Magda Piatkowska & Clara Higuera

BBC

Talk Abstract: Slow burning, ground breaking and blockbuster data applications at the BBC. Optimising demand and resources for data science, data engineering and analytics products in a large organisation.

Data solutions is a growing team within BBC. We are using machine learning to solve strategic problems and serve our audience better. In this talk we would like to share our experience in driving demand and managing resources to deliver on the promise machine learning is making. Some projects take a long time to take off while others skyrocket in matter of weeks. We will present a broad variety of projects and their life cycle in a large corporation like BBC, including development of a one specific component that turned into a versatile methodology for multiple purposes and services: from building audience segmentations to content similarity recommenders and investigating the existence of political knowledge gaps. Project that is serving a wide variety of stakeholders within BBC and academia. 

Bio: Magda is an engineer and computer scientist from trade. Over recent years, she has become a technology leader specialising in data and AI driven change in media. She managed multi-million investments in technology delivering digital change in large scale newsrooms (>100) across public and private sectors. She managed global data teams in the USA, Ireland and currently UK (previously to BBC, in The Telegraph and Channel 4). Magda also represents industry in public debate about adoption of AI as a member of data science committee of the Royal Statistical Society.

Bio: Clara Higuera Cabañes graduated in Computer Science from the Complutense University in Madrid, afterwards she carried out her PhD in Artificial Intelligence and Bioinformatics. Her thesis was focused on the application of machine learning methods for the study of metabolism. During her PhD she carried out research stays in US and Sweden and published several papers in international journals. After her PhD she became interested in Data Science in industry and worked for a while in a start up on line newspaper in Spain. Now she works at BBC as data scientist applying the techniques she learnt during her PhD to help better understand BBC audiences, make decisions based on data and build data products.

 

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